Data Engineering Podcast

SEPTEMBER 2, 2019

Summary Data professionals are working in a domain that is rapidly evolving. In order to stay current we need access to deeply technical presentations that aren’t burdened by extraneous marketing. To fulfill that need Pete Soderling and his team have been running the Data Council series of conferences and meetups around the world. In this episode Pete discusses his motivation for starting these events, how they serve to bring the data community together, and the observations that he has ma

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Building Data Database Design Media 100

KDnuggets

SEPTEMBER 5, 2019

This blog summarizes the career advice/reading research papers lecture in the CS230 Deep learning course by Stanford University on YouTube, and includes advice from Andrew Ng on how to read research papers.

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Pandora Engineering

SEPTEMBER 6, 2019

When embarking on the journey of developing a new application, a team must establish the foundational technologies upon which their… Continue reading on Algorithm and Blues »

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Teradata

SEPTEMBER 2, 2019

Companies are increasingly exploring opportunities to apply reinforcement learning to their most challenging problems. Learn what applications work the best.

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Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data

Confluent

SEPTEMBER 5, 2019

TL;DR. Following on from How to Work with Apache Kafka in Your Spring Boot Application , which shows how to get started with Spring Boot and Apache Kafka ® , here I will demonstrate how to enable usage of Confluent Schema Registry and Avro serialization format in your Spring Boot applications. Using Avro schemas, you can establish a data contract between your microservices applications.

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KDnuggets

SEPTEMBER 3, 2019

These three deep learning frameworks are your go-to tools for NLP, so which is the best? Check out this comparative analysis based on the needs of NLP, and find out where things are headed in the future.

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Deep Learning 122

Teradata

SEPTEMBER 5, 2019

4D analytics combines geospatial, temporal and time series data to do advanced analysis of time and space. Learn how to uncover new insights today.

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Data 56

Confluent

SEPTEMBER 6, 2019

First, what is event sourcing? Here’s an example. Consider your bank account: viewing it online, the first thing you notice is often the current balance. How many of us drill down to see how we got there? We probably all ask similar questions such as: What payments have cleared? Did my direct deposit hit yet? Why am I spending so much money at Sephora?

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KDnuggets

SEPTEMBER 4, 2019

A recurring subject in NLP is to understand large corpus of texts through topics extraction. Whether you analyze users’ online reviews, products’ descriptions, or text entered in search bars, understanding key topics will always come in handy.

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Python 121

Rockset

SEPTEMBER 6, 2019

"A fast-moving technology field where new tools, technologies and platforms are introduced very frequently and where it is very hard to keep up with new trends." I could be describing either the VR space or Data Engineering, but in fact this post is about the intersection of both. Virtual Reality – The Next Frontier in Media I work as a Data Engineer at a leading company in the VR space, with a mission to capture and transmit reality in perfect fidelity.

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Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Engineering

Teradata

SEPTEMBER 5, 2019

4D analytics combines geospatial, temporal and time series data to do advanced analysis of time and space. Learn how to uncover new insights today.

Data 40

Data 40

KDnuggets

SEPTEMBER 4, 2019

Recommender systems are an important class of machine learning algorithms that offer "relevant" suggestions to users. Categorized as either collaborative filtering or a content-based system, check out how these approaches work along with implementations to follow from example code.

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KDnuggets

SEPTEMBER 5, 2019

This is an interview between Rosaria Silipo and data scientists Paolo Tamagnini, Simon Schmid and Christian Dietz, asking a few questions on the topic of automated machine learning from their point of view, and some interesting examples of its practical use.

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KDnuggets

SEPTEMBER 4, 2019

In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models.

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Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

Building

KDnuggets

SEPTEMBER 3, 2019

In this tutorial, you will learn how to run task scheduler to web scrape data from Lazada (eCommerce) website and dump it into SQLite RDBMS Database.

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Python Database Data IT 115

KDnuggets

SEPTEMBER 6, 2019

Instead of focusing on skills thought to be required of data scientists, we can look at what they have actually done before.

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Data Data Science 121

KDnuggets

SEPTEMBER 6, 2019

From asking the best questions about data to answering those questions with certainty, understanding the value of these two seemingly different professions is clarified when you see how they should work together.

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Data 93

KDnuggets

SEPTEMBER 2, 2019

Without a well-defined approach for collecting and structuring training data, launching an AI initiative becomes an uphill battle. These six recommendations will help you craft a successful strategy.

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KDnuggets

SEPTEMBER 2, 2019

In this article, we will consider the most vivid data science use cases in the industry of energy and utilities.

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Utilities Data Science Data 112

KDnuggets

SEPTEMBER 3, 2019

DataScienceGO returns to San Diego Sep 27-29, for a three-day career-focused conference designed to unite newcomers, practitioners, managers and executives under one umbrella, speakers weigh in on how to forge the best teams, increase your hiring chances, and prepare for the future.

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KDnuggets

SEPTEMBER 5, 2019

Managing human bias is an important part of the analytics process. Learn about three areas to watch out for to ensure your models as unbiased as possible.

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Process Management 88

KDnuggets

SEPTEMBER 6, 2019

Hone your practical speech recognition application skills with this overview of building a voice assistant using Python.

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Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

Building

KDnuggets

SEPTEMBER 3, 2019

The quest for recreating cognitive capabilities of the brain in deep neural networks remains one of the elusive goals of AI. Let’s explore some human cognitive skills that are serving as inspiration to a new generation of AI techniques.

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KDnuggets

SEPTEMBER 4, 2019

Save 40% on Get Programming with Python, Data Science with Python and Dask, and Learn Quantum Computing with Python and Q# with code nlpython40.

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Python Data Science Programming Coding 80

KDnuggets

SEPTEMBER 4, 2019

Also: The secret sauce for growing from a data analyst to a data scientist; 4 Tips for Advanced Feature Engineering and Preprocessing; R Users’ Salaries from the 2019 Stackoverflow Survey; Emoji Analytics.

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Architecture Engineering Data 68

KDnuggets

SEPTEMBER 4, 2019

This week: Object-oriented programming for data scientists; Deep Learning Next Step: Transformers and Attention Mechanism; R Users' Salaries from the 2019 Stackoverflow Survey; Types of Bias in Machine Learning; 4 Tips for Advanced Feature Engineering and Preprocessing; and much more!

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Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

Certification

KDnuggets

SEPTEMBER 5, 2019

In this TensorFlow tutorial, you’ll learn the impact of optimizing both operators and entire graphs, how to efficiently organize data in training and testing datasets to minimize data shuffling, and how to identify a well-optimized model using Anaconda and ActivePython.

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Datasets Data 52

KDnuggets

SEPTEMBER 2, 2019

Also: Types of Bias in Machine Learning; Deep Learning Next Step: Transformers and Attention Mechanism; New Poll: Data Science Skills; R Users Salaries from the 2019 Stackoverflow Survey; How to Sell Your Boss on the Need for Data Analytics.

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KDnuggets

SEPTEMBER 6, 2019

See how creating a system of purpose-specific displays enables users to quickly get answers to their data-related questions.

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KDnuggets

SEPTEMBER 2, 2019

KDnuggets cartoon looks at how AI will impact Labor Day in the year 2050.

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